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1 DTV is neither PAL nor NTSC The values are placed in the NTSC rows for convenience 2 Wide aspect ratios (178 and 235) for VHS, LD, and VCD assume a letterboxed picture For comparison, letterboxed 166 aspect ratio resolution is about seven percent higher than 178 Letterbox is also assumed for DVD and DTV at a 235 aspect ratio DVD s native aspect ratio is 133; it uses anamorphic mode for 178 DTV s native aspect ratio is 178 3 The very rare 178 anamorphic LD has the same pixel count as 133 LD Anamorphic LD letterboxed to 235 has almost the same pixel count as 178 LD (567 363) The mostly non-existent 178 anamorphic VHS has the same pixel count as 133 VHS Anamorphic VHS letterboxed to 235 has almost the same pixel count as 178 VHS (333 363) No commercial 235 anamorphic format exists and no corresponding stretch mode exists on widescreen TVs 4 TVL is lines of horizontal resolution per picture height For analog formats, the customary value is used; for digital formats, the value is derived from the actual horizontal pixel count adjusted for the aspect ratio DVD s horizontal resolution is lower for 178 because the pixels are wider Pixels for VHS and LD are approximations based on TVL and scan lines 5 Resolutions refer to the medium, not the display If a DVD player performs automatic letterboxing on a 185 movie (stored in 178), the displayed vertical resolution on a standard 133 TV is the same as from a letterboxed LD (360 lines)

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It is interesting to examine the learned weight values for the 2899 weights in the network Figure 410 depicts the values of each of these weights after one iteration through the weight update for all training examples, and again after 100 iterations To understand this diagram, consider first the four rectangular blocks just below the face images in the figure Each of these rectangles depicts the weights for one of the four output units in the network (encoding left, straight, right, and up) The four squares within each rectangle indicate the four weights associated with this output unit-the weight wo, which determines the unit threshold (on the left), followed by the three weights connecting the three hidden units to this output The brightness of the square indicates the weight value, with bright white indicating a large positive weight, dark black indicating a large negative weight, and intermediate shades of grey indicating intermediate weight values For example, the output unit labeled "up" has a near zero wo threshold weight, a large positive weight from the first hidden unit, and a large negative weight from the second hidden unit The weights of the hidden units are shown directly below those for the output units Recall that each hidden unit receives an input from each of the 30 x 32 image pixels The 30 x 32 weights associated with these inputs are displayed so that each weight is in the position of the corresponding image pixel (with the wo threshold weight superimposed in the top left of the array) Interestingly, one can see that the weights have taken on values that are especially sensitive to features in the region of the image in which the face and body typically appear The values of the network weights after 100 gradient descent iterations through each training example are shown at the bottom of the figure Notice the leftmost hidden unit has very different weights than it had after the first iteration, and the other two hidden units have changed as well It is possible to understand to some degree the encoding in this final set of weights For example, consider the output unit that indicates a person is looking to his right This unit has a strong positive weight from the second hidden unit and a strong negative weight from the third hidden unit Examining the weights of these two hidden units, it is easy to see that if the person's face is turned to his right (ie, our left), then his bright skin will roughly align with strong positive weights in this hidden unit, and his dark hair will roughly align with negative weights, resulting in this unit outputting a large value The same image will cause the third hidden unit to output a value.

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Format VCD (178) Horizontal pixels 352 Vertical pixels Total pixels x VCD (16:9) x VCD (4:3) x VHS (16:9) x VHS (4:3) x LD (16:9) x LD (4:3) x DVD (16:9/4:3) x DTV3 (16:9) 180 63,360 VCD (133) 352 240 84,480 4:3 VHS (178) 333 360 119,880 189 142 VHS (133) 333 480 159,840 252 189 4:3 LD (178) 567 360 204,120 322 242 170 128 LD (133) 567 480 272,160 430 322 227 170 4:3 DVD (178/133) 720 480 345,600 545 409 288 216 169 127 DTV3 (178) 1280 720 921,600 1455 1091 769 577 451 339 267 DTV4 (178) 1,920 1,080 2,073,600 3273 2455 1730 1297 1016 762 600 225

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As noted earlier, gradient descent can be performed for any function E that is differentiable with respect to the parameterized hypothesis space While the basic BAcWROPAGATION algorithm defines E in terms of the sum of squared errors of the network, other definitions have been suggested in order to incorporate other constraints into the weight-tuning rule For each new definition of E a new weight-tuning rule for gradient descent must be derived Examples of alternative definitions of E include

9:

Note: 16:9 aspect ratios for VHS, LD, and VCD are letterboxed in a 4:3 picture Comparisons between different aspect ratios are not as meaningful These are shown in italics Comparisons at 185 or 235 aspect ratios are essentially the same as at 178 (16:9)

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